Faculty Of Computer Science Research Paper

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Browsing Faculty Of Computer Science Research Paper by Author "12613"

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    Gaining-sharing knowledge based algorithm for solving optimization problems: a novel nature-inspired algorithm
    (Springer, 2019) Mohamed A.W.; Hadi A.A.; Mohamed A.K.; Operations Research Department; Faculty of Graduate Studies for Statistical�Research; Cairo University; Giza; 12613; Egypt; Wireless Intelligent Networks Center (WINC); School of Engineering and Applied Sciences; Nile University; Giza; Egypt; College of Computing and Information Technology; King Abdulaziz University; P. O. Box 80200; Jeddah; 21589; Saudi Arabia; Department of Computer Science; Faculty of Computer Science; October University for Modern Sciences and Arts (MSA); 6th October City; Giza; 12451; Egypt
    This paper proposes a novel nature-inspired algorithm called Gaining Sharing Knowledge based Algorithm (GSK) for solving optimization problems over continuous space. The GSK algorithm mimics the process of gaining and sharing knowledge during the human life span. It is based on two vital stages, junior gaining and sharing phase and senior gaining and sharing phase. The present work mathematically models these two phases to achieve the process of optimization. In order to verify and analyze the performance of GSK, numerical experiments on a set of 30 test problems from the CEC2017 benchmark for 10, 30, 50 and 100 dimensions. Besides, the GSK algorithm has been applied to solve the set of real world optimization problems proposed for the IEEE-CEC2011 evolutionary algorithm competition. A comparison with 10 state-of-the-art and recent metaheuristic algorithms are executed. Experimental results indicate that in terms of robustness, convergence and quality of the solution obtained, GSK is significantly better than, or at least comparable to state-of-the-art approaches with outstanding performance in solving optimization problems especially with high dimensions. � 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
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    Hybrid Algorithm for Rough Multi-level Multi-objective Decision Making Problems
    (International Information and Engineering Technology Association, 2019) El-Feky S.F.; Abou-El-Enien T.H.M.; Faculty of Computer Science; Department of Computer Science; Modern Science and Arts University; Giza; 12613; Egypt; Department of Operations Research and Decision Support; Faculty of Computers and Information; Cairo University; Giza; 12613; Egypt
    The purpose of this paper is to generate compromise solutions for the multi-level multiobjective decision making (MLMODM) problems with rough parameters in the objective functions (RMLMODM) based on TOPSIS method and "Lower & Upper� approximations method. We introduce a computational hybrid algorithm for solving RMLMODM problems. Also, we solved illustrative numerical example and compared the solution of the proposed algorithm with the solution of Global Criterion (GC) method. The engineers and the scientists can apply the introduced hybrid algorithm to various practical RMLMODM problems to obtain numerical solutions. � 2019 Lavoisier. All rights reserved.